Buttons, GPT, DZAMO or a manager
Four ways to handle inbound enquiries. The right one depends on how your clients write, what has to happen in the CRM, and at which point the conversation needs a human.
Which approach fits your job
A chatbot builder
Walks the client through fixed steps. Good for menus, quizzes and bookings.
Example: “Choose a service → choose a date → leave your phone number”.
A GPT prototype
A fast way to check how a model understands your materials and answers common questions.
Example: upload the price list and test 20 real client questions in a sandbox chat.
The DZAMO AI sales system
Runs on real channels and a real CRM, with voice notes, photos, PDFs, pricing, handoff to a manager and failure monitoring.
Example: at night the client sends a voice note and a floor plan. The system answers, saves the summary to the CRM and brings in a manager.
A manager
Negotiates flexibly, makes decisions and owns the deal. They can also be busy, miss an enquiry, forget to reply, or simply have finished for the day.
Example: three enquiries land at 10:30 pm at once. The clients wait until morning.
What to check before you launch anything
Ask to be shown five things: where the prices come from, who finds out about a failure, when a human takes over, how the rules get updated, and who owns the system after launch.
| Question | What to verify |
|---|---|
| Prices | Where does the number come from? What happens if the data is missing or out of date? |
| Failures | Who learns that a message was not delivered, the model did not answer, or the CRM did not record the data? |
| The line | When does the system call a human? What does the manager see at handoff? |
| Changes | How are price lists updated? How are new rules tested before they go live? |
| Ownership | Who investigates an error after launch, and how quickly? |
How we lower the cost of a mistake
Prices from the source
The system works from the client's own documents, price lists and rules. If the data for an answer is missing, the question goes to a manager.
Alerts on failures
Message delivery, channel errors and handoffs to managers are each monitored separately.
Every change is verified
The engine carries 64,000 lines of tests covering conversations, integrations and production scenarios.
This is a large product system, and we keep developing it on real sales.
Questions about choosing an approach
When is a chatbot builder enough?
When the client follows a short, predictable route: pick a service, pick a date, leave a phone number. Buttons handle that well.
When do you need a custom AI sales system?
When clients write in their own words, send voice notes, photos and documents, ask for a quote, and the data has to reach the CRM and then a manager.
Can we just add GPT to our builder?
You can, and such a prototype quickly shows how the model answers from your materials. A production launch still needs channels, CRM, handoff, monitoring and tests configured separately.
We already have a button bot. What do we do with it?
Keep the button route for bookings and service selection, and pass free-form questions to the AI system.
Let us start from your process
Show us the current flow and some live conversations. We will pick the right way to handle your inbound.